Geographical Job Scheduling in Data Centers with Heterogeneous Demands and Servers

Xingjian Lu, Fanxin Kong, Jianwei Yin, Xue Liu, Huiqun Yu, Guisheng Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

The fast proliferation of cloud computing promotes the rapid development of large-scale commercial data centers. Tens or even hundreds of geographically distributed data centers have been deployed for better reliability and quality of services. This brings huge energy consumption for data centers. Previous research has proved that the geographical load balancing technique can achieve significant energy cost savings for geographically distributed data centers. However, existing methods for geographical load balancing often assume data centers with homogeneous servers, and workloads with single-dimension or uniform resource demands. This is an over-simplification in reality, especially when modern data centers are typically constructed from a variety of server classes. In this paper, we systematically study the problem of job scheduling for geographically distributed data centers to embrace the heterogeneity of underlying platforms and workloads. We develop a novel distributed algorithm to solve the problem efficiently based on the alternating direction method of multipliers. Extensive evaluations based on real-life data center topology, traffic traces, and electricity price data show high efficiency and efficacy of our method.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015
EditorsCalton Pu, Ajay Mohindra
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages413-420
Number of pages8
ISBN (Electronic)9781467372879
DOIs
StatePublished - Aug 19 2015
Externally publishedYes
Event8th IEEE International Conference on Cloud Computing, CLOUD 2015 - New York, United States
Duration: Jun 27 2015Jul 2 2015

Other

Other8th IEEE International Conference on Cloud Computing, CLOUD 2015
CountryUnited States
CityNew York
Period6/27/157/2/15

ASJC Scopus subject areas

  • Computer Networks and Communications

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    Lu, X., Kong, F., Yin, J., Liu, X., Yu, H., & Fan, G. (2015). Geographical Job Scheduling in Data Centers with Heterogeneous Demands and Servers. In C. Pu, & A. Mohindra (Eds.), Proceedings - 2015 IEEE 8th International Conference on Cloud Computing, CLOUD 2015 (pp. 413-420). [7214072] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLOUD.2015.62